python

Computational data science notebooks to foster development studies.

Through the lens of a multiscale geographically weighted regression (MGWR) and an updated inference framework, we assess the spatial scale at which political and socioeconomic factors affect violence.

This paper introduces a user-friendly geocomputational notebook that illustrates how to process and analyze satellite NTL images.

An interactive geocomputational notebook to study spatial clusters and outliers

A geocomputational notebook to study spatial heterogeneity using the GWR and MGWR frameworks.

An introduction to how to construct, explore, and export spatial connectivity structures (W) using Python.

A geocomputational notebook to monitor subnational human development using Python. Besides exploratory data analysis, the notebook introduces geospatial mapping, spatial dependence, and spatial inequality.

A geocomputational notebook to monitor spatial inequality dynamics.

A geocomputational notebook to monitor regional development in Bolivia using Python. Besides exploratory data analysis, the notebook introduces geospatial mapping, spatial dependence, spatial inequality, and spatial heterogeneity.

An introduction to the Solow growth model and its convergence prediction